Yield Farming Analysis
SkillSecurityAnalyze DeFi yield farming opportunities including APY breakdown, risk assessment, smart contract security, and impermanent loss estimation.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Yield Farming Analysis skill
What this skill tells your AI
The instructions your AI receives, as published by nirholas/three.ws in data/skills/defi/yield-farming-analysis/SKILL.md and read by ahel’s review.
When to use this skill
Use when the user asks about:
- Evaluating yield farming opportunities
- Comparing DeFi yields across protocols
- Assessing farming risks and sustainability
- Calculating impermanent loss for a token pair
- Finding the best yield for a given asset or pair
Analysis Framework
1. Opportunity Overview
Gather and present:
- Protocol name, chain, and deployment history
- Pool composition (token pair or single-sided)
- Current APY/APR with base vs incentive breakdown
- TVL (Total Value Locked) and recent trend
- Pool age and historical APY stability over 7d, 30d, 90d
2. Yield Breakdown
Decompose the advertised yield into:
- Base trading fee APY — derived from actual volume
- Incentive token APY — farming reward emissions
- Compounding frequency — auto-compound available?
- Sustainability check — review emissions schedule, token inflation rate, and runway
- Comparative yield — how does this compare to similar pools on other protocols?
3. Risk Assessment
Evaluate each factor systematically:
| Risk Factor | What to Check |
|---|---|
| Smart contract audit status | Audited by reputable firm? Multiple audits? |
| Protocol TVL trend | Growing, stable, or declining over 30d? |
| Token emission schedule | Inflationary pressure on reward token? |
| Impermanent loss exposure | High volatility pair or correlated assets? |
| Admin key risk | Multisig with timelock? Or single EOA? |
| Oracle dependency | Which oracle? Redundancy? |
| Liquidity depth | Can the user exit at size without significant slippage? |
| Chain risk | Bridge dependencies, L2 sequencer risk? |
4. Impermanent Loss Estimation
For the given token pair, calculate IL scenarios:
- Retrieve current price ratio between the two assets
- Pull historical volatility (30d and 90d)
- Compute correlation coefficient if data available
- Present IL at these price divergence levels:
- ±10% divergence: ~0.11% IL
- ±25% divergence: ~0.6% IL
- ±50% divergence: ~2.0% IL
- ±100% divergence: ~5.7% IL
- Compare estimated IL against yield to determine net profitability
5. Output Format
Provide a structured recommendation:
- Protocol: Name and chain
- Pool: Token pair and fee tier
- Current APY: X% (base Y% + rewards Z%)
- Verdict: Strong / Moderate / Weak / Avoid
- Expected net APY: After estimated IL
- Risk level: Low / Medium / High / Very High
- Suggested allocation: Percentage of portfolio (never more than 10% in a single farm)
- Minimum lock awareness: Any withdrawal fees or lock periods
- Exit conditions: Specific triggers for when to withdraw (reward token drops X%, TVL drops below Y, APY falls below Z)
Signals
- GitHub stars
- 114
- Forks
- 29
- Last commit
- Sep 2026
Advanced
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yield-farming-analysis- Source
- github.com/nirholas/three.ws